Within any communication medium, there is always a trade-off between reaching a broad audience and ensuring the relevance of a message for its individual recipients within that audience. If the message is one that is relevant for a very large user community, and the user community is well defined, then the message originator can efficiently deliver the message to that community through conventionally defined and understood methods. However, when the message is relevant for only a subset of the large, well-defined user community, then delivery of an appropriate message is much more challenging and less efficient.
A real-world analogy of this concept is related to announcements at a dinner party. If an announcement is made to signal the beginning of a toast, then the message is efficient because most of the recipients of the message will find it relevant. If, on the other hand, the announcement is made that a particular vehicle's lights have been left on, then the message is considered very inefficient in that only a few recipients in the room (the driver and any potential passengers) will find the message relevant.
More generally, because of the diminished efficiency that is involved in sending limited relevance messages, limited relevance message senders may have a desire to discover the subset of users within the community that will find the message relevant. The traditional mechanisms used to discover that particular subset of users within the community are more difficult or less efficient than sending the limited-relevance message to the broader audience because the message sender must first define criteria to determine whether a message would be relevant to a potential message recipient and then the message sender must evaluate each potential message recipient against the criteria.
To continue the analogy, the message sender could potentially attempt to discover the relevant recipient of the message in a number of ways. The sender could, for example, make an announcement to the crowd that he is looking for the owner of a particular car. Of course, this message adds complexity to the conversation because this new message is no more efficient than the “headlight” message, and, in fact, adds another communication round trip to the message sequence. Another approach that the sender might take is to question each member of the party individually. When defining the criteria used to evaluate the message relevance, the message sender may ask individual guests if they arrived in the particular model of car whose headlights are on. Then the message sender could ask each person attending the party what model of car they arrived in, and based on that result, may decide to inform that particular attendee that their headlights should be checked. From an efficiency perspective, the number of recipients of an unrelated message would be, on average, ½*(number of guests), which is more efficient in one measure (the number of people receiving the message), but the time to deliver the message would be, on average, (time to deliver message)*½*(number of guests), as compared to (time to deliver message) when broadcast once to the room of guests. From a time perspective, this approach is very inefficient.
What is needed, in the general case, is a way to identify (1) the subgroup for which the message is relevant, and (2) incentives for relaying messages to intended recipients. This identification can be performed by analysis of (a) associative artifacts not necessarily related to the conversation at hand, but which can be collected from the surrounding environment, (b) any communications history that might already be available, or (c) some combination of both (a) and (b). These artifacts can then be synthesized in a way that allows the message sender to change the communications medium or message in order to ensure that the message delivery is efficient.